DESCRIPTION:(provided by the applicant) Stimulus encoding by sensory neurons is often viewed as feature detection by template matching. In these models, each neuron responds to its preferred input pattern with its highest firing rate. This perspective has several disadvantages: 1) Stimulus specificity-each neuron optimally encodes only one stimulus. 2) Response ambiguity-various non-optimal stimuli evoke identical responses. 3) Behavioral significance- task-linked and irrelevant stimuli are the same. We have recently proposed a link between spatio-temporal structure and population encoding that has the prospect of overcoming the difficulties of the feature matching/rate coding approach. We hypothesized that stimulus attributes are represented by the firing patterns of distributed networks of cortical neurons. Such networks, termed predictive coding networks, can make extensive use of feedback to learn their receptive fields from the statistics of input stimuli. We propose to test this hypothesis in studies of neurons in macaque dorsal extrastriate visual cortex. Visual motion processing in areas MT and MST provide an ideal setting for testing models of neural coding as the relevant stimuli are complex, time varying, and are used in naturalistic behaviors. We will first develop a predictive coding model of MST responses to local motion stimuli and full-field optic flow. We will then test that model by determining whether the predicted effects of MST feedback on MT neuronal responses are consistent with the predictive coding model. Next we will measure the responses of MST cells when visual stimuli are combined with self-movement and pursuit targets. Finally, we will engage the monkey in stimulus linked behavioral tasks to determine whether population-distributed synchrony might identify stimulus and task effects in MT and MST responses. MT-MST responses are well-described in an extensive literature that has failed to explain the receptive field mechanisms or higher-order visual motion responses in MST. Our collaborative development of a detailed model of MT-MST spike trains will directly test our model and elucidate the cortical mechanisms of motion perception.